The document describes a Hadoop infrastructure implemented at the Laboratory for E-business at the University of Belgrade to manage large datasets for education. A three node Hadoop cluster was set up and integrated with the Moodle learning management system. The cluster includes a master node to manage performance and one data node. Data replication is used to preserve data across nodes. The goal is to improve education by enabling efficient and reliable manipulation of large and diverse sources of data.

1. University of Belgrade
Faculty of Organizational Sciences
Laboratory for E-business
HADOOP INFRASTRUCTURE FOR
EDUCATION
Darko Marjanović, darko@elab.rs
Miloš Milovanović, milovanovicm@elab.rs
Božidar Radenković, boza@elab.rs

2. Laboratory for E-business
• Exists within the Faculty of Organizational Sciences, University of
Belgrade
• Organizes e-learning courses since 2001. by using Moodle LMS and
blended learning concept
• More than 1000 students take our courses each year
• Research areas:
 E-business
 Internet and mobile technologies
 Big Data
 Cloud Computing
 E-education
 Adaptive e-services
 Internet of things
 Social media

3. Overview
• Introduction
• Hadoop model for education
• Implementation
• Cluster organizaton
• Conclusion

4. Introduction
• Education institutions need to have access to relevant information in
order to offer high-quality education to students.
• Main problem – Information arrive to organizations
• from variety of sources
• with rapidly increasing speed
• in variety of types.
• Hadoop as a possible solution to this matter

5. Hadoop
• Apache Hadoop is an open-source software framework for storage
and large-scale processing of data-sets on clusters of commodity
hardware.
• All the modules in Hadoop are designed with a fundamental
assumption that hardware failures are common and thus should be
automatically handled in software by the framework.

6. Big Data
• Big data is a blanket term for any collection of data sets so large
and complex that it becomes difficult to process using on-hand
database management tools or traditional data processing
applications.

7. Hadoop model for education
Guidelines used for deploying Hadoop model:
• Efficient data import
• Reliable manipulation
• Flexible output

8. Model for managing Big Data in
educational institutions

9. Implementation
• Three node cluster
• Integration with Moodle LMS
• Distributed storage
• In its performance, Hadoop cluster consumes a significant amount
of resources, and controlling them is inevitable.

10. Implemented Hadoop e-learning
infrastructure

11. Cluster organization
• Central role that is responsible for Hadoop’s performance is
represented by Master node.
• In order to optimize Hard Disk Drive Memory, the implementation
described here contains Data Node installed on the Master Node
• Imposed mechanism for preventing data losing between nodes is to
constantly monitor network infrastructure.
• Data replication as a mechanism for preserving data within cluster

12. Hadoop cluster organization in
Laboratory for E-business

13. Conclusion
• A scalable platform that brings Big Data based on Hadoop to e-learning
environment is presented.
• Main contribution of described paper is providing environment for
manipulating data generated from variety of sources in education
activities.
• Primary objective is improvement of e-learning process.
• Future research is directed to:
-optimizing integration with e-learning services
-integration with cloud platform

14. University of Belgrade
Faculty of Organizational Sciences
Laboratory for E-business
HADOOP INFRASTRUCTURE FOR
EDUCATION
Darko Marjanović, darko@elab.rs
Miloš Milovanović, milovanovicm@elab.rs
Božidar Radenković, boza@elab.rs